| Reference : A Biomolecular Isolation Framework for Molecular Eco-Systems Biology |
| Scientific congresses, symposiums and conference proceedings : Poster | |||
| Life sciences : Environmental sciences & ecology Life sciences : Microbiology | |||
| http://hdl.handle.net/10993/19399 | |||
| A Biomolecular Isolation Framework for Molecular Eco-Systems Biology | |
| English | |
Muller, Emilie  [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| Roume, Hugo [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| Shah, Pranjul [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| Wilmes, Paul [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| 2012 | |
| No | |
| International | |
| 112th General Meeting of the American Society for Microbiology | |
| from 16-06-2012 to 19-06-2012 | |
| [en] With the advent of high-throughput omic technologies, powerful and sensitive methods are available for the analysis of nucleic acid, protein and small molecule complements obtained from biological samples. Molecular eco-systems biology studies based on the integration of genomic, transcriptomic, proteomic and metabolomic data are faced with major challenges arising from the complexity, dynamics and heterogeneity of mixed microbial consortia. In order to facilitate meaningful data integration, analysis and modeling, it is essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single unique samples.
We have developed a new methodological framework for the reproducible isolation of high-quality genomic DNA, large and small RNA, proteins, and polar and non-polar metabolites from single unique mixed microbial community samples. The methodology is based around reproducible cryogenic sample preservation and cell lysis. Metabolites are extracted first using organic solvents, followed by the sequential isolation of nucleic acids and proteins using chromatographic spin column technology. The methodology was validated by comparison to traditional dedicated and simultaneous biomolecular isolation methods. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological, environmental and medical interest. Importantly, the developed methodology will allow exploitation of the inherent heterogeneity and dynamics within microbial consortia through spatial and temporal sampling of biological systems to allow later deconvolution of community-wide, population-wide and individual-level processes using the generated omic data. This approach has the potential to identify associations between distinct biomolecules and which may provide pointers towards unravelling previously unknown metabolic processes. Finally, by providing a standardized workflow, the methodology lays the foundation for comparative eco-systematic studies of different natural microbial consortia in the future. | |
| http://hdl.handle.net/10993/19399 |
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